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OCTIS (Terragni et al., 2021a, Optimizing and. Comparing is Simple!) is an open-source evalu- ation framework for the comparison of topic mod- els, that allows ...
In this paper, we present OCTIS, a framework for training, analyzing, and comparing Topic Models, whose optimal hyper-parameters are estimated using a Bayesian ...
OCTIS is an open-source framework for training, evaluating and comparing Topic Models. This tool uses single-objective Bayesian Optimization (BO) to ...
OCTIS (Optimizing and Comparing Topic models Is Simple) aims at training, analyzing and comparing Topic Models, whose optimal hyperparameters are estimated ...
OCTIS is an open-source framework for training, evaluating and comparing Topic Models. This tool uses single-objective Bayesian Optimization (BO) to optimize ...
OCTIS 2.0: Optimizing and Comparing Topic Models in Italian Is Even Simpler! S. Terragni, and E. Fersini. CLiC-it, volume 3033 of CEUR Workshop Proceedings ...
OCTIS allows researchers and practitioners to have a fair comparison between topic models of interest, using several benchmark datasets and well-known ...
Missing: 2.0: Italian Even
OCTIS: Comparing and optimizing topic models is simple! S Terragni, E Fersini, BG Galuzzi, P Tropeano, A Candelieri. Proceedings of the 16th Conference of the ...
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Apr 19, 2021 · In this paper, we present OCTIS, a framework for training, analyzing, and comparing Topic. Models, whose optimal hyper-parameters are.
Missing: 2.0: Even Simpler!
May 3, 2023 · Preprocess your own dataset or use one of the already-preprocessed benchmark datasets. • Well-known topic models (both classical and neurals).